麻豆官网

Houle, Elizabeth听¹听;听Kasprzyk, Joseph听²听;听Livneh, Ben听³

¹听CU 麻豆官网
²听CU 麻豆官网
³听颁滨搁贰厂

In the western United States, water resource management is increasingly reliant on numerical modeling of hydrological processes, namely snow accumulation and ablation. We seek to advance a framework for providing model diagnostics for such systems by combining an improved understanding of model structural differences (i.e., conceptual vs. physically based) and parameter sensitivities. The two snow models used in this study are SNOW-17, a conceptual degree-day model, and the Variable Infiltration Capacity (VIC) snow model, which is physically based and solves the full water and energy balances. To better understand the performance of these models, global sensitivity analysis and multi objective calibration methods were applied to identify important parameters and show calibrated parameter values. For the physically based model, we contribute a novel exploration of some parameters that can be adjusted within the model, including the liquid water holding capacity, the density of newly fallen snow, snow roughness, and snow albedo decay parameters. For each model run, snow sensitivities and errors (i.e., snow water equivalent results) are visualized to better understand the effect of changing parameters on model outputs. Additionally, a temperature change analysis was conducted for each model to explore model sensitivity with respect to temperature change. Accurately predicting water yield is essential for water management, and it is used here as a practical measure to determine the importance of model parameter sensitivity and calibration. The analysis was conducted across a range of snow-dominated locations representing a variety of climates across the western United States (e.g. continental, maritime, intermountain).